Abstract: The disclosure provides an approach for rendering heterogeneous polydisperse granular media. In one aspect, a rendering application renders such granular media using a combination of explicit path tracing and accelerated path construction using proxy path tracing, shell tracing, and volumetric path tracing. In proxy path tracing in particular, the rendering application instantiates proxy geometry in the form of a bounding sphere and determines internal scattering in the grain using a precomputed grain scattering distribution function that relates incident and outgoing radiance functions on the bounding sphere. In shell tracing, the rendering application uses shells to aggregate many grain interactions into a single step.

Abstract: Supervised machine learning using neural networks is applied to denoising images rendered by MC path tracing. Specialization of neural networks may be achieved by using a modular design that allows reusing trained components in different networks and facilitates easy debugging and incremental building of complex structures. Specialization may also be achieved by using progressive neural networks. In some embodiments, training of a neural-network based denoiser may use importance sampling, where more challenging patches or patches including areas of particular interests within a training dataset are selected with higher probabilities than others. In some other embodiments, generative adversarial networks (GANs) may be used for training a machine-learning based denoiser as an alternative to using pre-defined loss functions.

Abstract: Supervised machine learning using convolutional neural network (CNN) is applied to denoising images rendered by MC path tracing. The input image data may include pixel color and its variance, as well as a set of auxiliary buffers that encode scene information (e.g., surface normal, albedo, depth, and their corresponding variances). In some embodiments, a CNN directly predicts the final denoised pixel value as a highly non-linear combination of the input features. In some other embodiments, a kernel-prediction neural network uses a CNN to estimate the local weighting kernels, which are used to compute each denoised pixel from its neighbors. In some embodiments, the input image can be decomposed into diffuse and specular components. The diffuse and specular components are then independently preprocessed, filtered, and postprocessed, before recombining them to obtain a final denoised image.

Abstract: Supervised machine learning using neural networks is applied to denoising images rendered by MC path tracing. Specialization of neural networks may be achieved by using a modular design that allows reusing trained components in different networks and facilitates easy debugging and incremental building of complex structures. Specialization may also be achieved by using progressive neural networks. In some embodiments, training of a neural-network based denoiser may use importance sampling, where more challenging patches or patches including areas of particular interests within a training dataset are selected with higher probabilities than others. In some other embodiments, generative adversarial networks (GANs) may be used for training a machine-learning based denoiser as an alternative to using pre-defined loss functions.

Abstract: Supervised machine learning using neural networks is applied to denoising images rendered by MC path tracing. Specialization of neural networks may be achieved by using a modular design that allows reusing trained components in different networks and facilitates easy debugging and incremental building of complex structures. Specialization may also be achieved by using progressive neural networks. In some embodiments, training of a neural-network based denoiser may use importance sampling, where more challenging patches or patches including areas of particular interests within a training dataset are selected with higher probabilities than others. In some other embodiments, generative adversarial networks (GANs) may be used for training a machine-learning based denoiser as an alternative to using pre-defined loss functions.

Abstract: The disclosure provides an approach for denoising (also referred to as “filtering”) rendered images. In one embodiment, a denoising application takes as input rendered images and feature buffers that encode image information such as surface positions, surface depths, surface normals, surface albedos, and distances to the camera. For each pixel in a received image, the denoising application performs a first-order regression in a predefined neighborhood of the pixel to find a linear combination of pixel features that fits pixel colors in the predefined neighborhood. In such a first-order regression, the local regression weight of each pixel in the neighborhood may be determined using a metric which computes distances based on color values in patches around pixels being compared. In another embodiment, collaborative filtering may be performed in which filtered output from the first-order regression in each neighborhood is averaged with filtered output from overlapping neighborhoods to obtain a final output.

Abstract: According to one implementation, an image rendering system includes a computing platform having a hardware processor and a system memory storing an image denoising software code. The hardware processor executes the image denoising software code to receive an image file including multiple pixels, each pixel containing multiple depth bins, and to select a pixel including a noisy depth bin from among the pixels for denoising. The hardware processor further executes the image denoising software code to identify a plurality of reference depth bins from among the depth bins contained in one or more of the pixels, for use in denoising the noisy depth bin, and to denoise the noisy depth bin using an average of depth bin values corresponding respectively to each of the reference depth bins.

Abstract: The disclosure provides an approach for rendering heterogeneous polydisperse granular media. In one aspect, a rendering application renders such granular media using a combination of explicit path tracing and accelerated path construction using proxy path tracing, shell tracing, and volumetric path tracing. In proxy path tracing in particular, the rendering application instantiates proxy geometry in the form of a bounding sphere and determines internal scattering in the grain using a precomputed grain scattering distribution function that relates incident and outgoing radiance functions on the bounding sphere. In shell tracing, the rendering application uses shells to aggregate many grain interactions into a single step.

Abstract: The disclosure provides an approach for denoising (also referred to as “filtering”) rendered images. In one embodiment, a denoising application takes as input rendered images and feature buffers that encode image information such as surface positions, surface depths, surface normals, surface albedos, and distances to the camera. For each pixel in a received image, the denoising application performs a first-order regression in a predefined neighborhood of the pixel to find a linear combination of pixel features that fits pixel colors in the predefined neighborhood. In such a first-order regression, the local regression weight of each pixel in the neighborhood may be determined using a metric which computes distances based on color values in patches around pixels being compared. In another embodiment, collaborative filtering may be performed in which filtered output from the first-order regression in each neighborhood is averaged with filtered output from overlapping neighborhoods to obtain a final output.

Abstract: According to one exemplary implementation, a method for use by a global illumination system including a hardware processor includes identifying, using the hardware processor, a first interior vertex of multiple first interior vertices of a light path, the first interior vertices being situated within a volume having a refractive boundary. In addition, the method includes determining, using the hardware processor, a surface vertex of the light path at the refractive boundary, and determining, using the hardware processor, a linear direction from the surface vertex to a light source of the light path. The method also includes determining, using the hardware processor, one or more second interior vertices for completing the light path by constructing a path from the surface vertex to the first interior vertex, based on the linear direction, the surface vertex and the first interior vertex.

Abstract: Techniques for illuminating an indoor scene. A directional distribution associated with the indoor scene is received. The indoor scene has a first scene element and a first quadrilateral. The first scene element has a first shading point disposed thereon. The directional distribution is reparametrized such that the first quadrilateral as viewed from the first shading point corresponds to an axis-aligned rectangular region in the reparametrized directional distribution. The scene element is illuminated using one or more samples drawn from the shading point by performing importance sampling based on the reparametrized directional distribution.

Abstract: Provided are methods of diagnosing IgA nephropathy in a subject. Optionally, the methods comprise isolating an IgG from the subject and determining whether the IgG binds to a galactose-deficient IgA1. Optionally, the methods comprise providing a biological sample from the subject and detecting in the sample a mutation in a IGH gene, wherein the mutation is in a nucleotide sequence encoding a complementarity determining region 3 (CDR3) of a IGH variable region. Optionally, the methods comprise determining a level of IgG specific for a galactose-deficient IgA1 in the subject. Also provided are methods of treating or reducing the risk of developing IgA nephropathy in a subject.

Abstract: According to one exemplary implementation, a method for use by a global illumination system including a hardware processor includes identifying, using the hardware processor, a first interior vertex of multiple first interior vertices of a light path, the first interior vertices being situated within a volume having a refractive boundary. In addition, the method includes determining, using the hardware processor, a surface vertex of the light path at the refractive boundary, and determining, using the hardware processor, a linear direction from the surface vertex to a light source of the light path. The method also includes determining, using the hardware processor, one or more second interior vertices for completing the light path by constructing a path from the surface vertex to the first interior vertex, based on the linear direction, the surface vertex and the first interior vertex.

Abstract: There is provided a system including a memory storing a software application and a processor configured to execute the software application to transmit a light through a scene, the scene including a medium described by an extinction function, define a fictitious medium described by a fictitious extinction function, determine a path through the medium, the path including a plurality of points, calculate one of a plurality of weights for each of the plurality of points, the one of the plurality of weights corresponding to one minus the ratio of the extinction function to the fictitious extinction function, and estimate a transmittance of the lights through the medium as a product of the plurality of weights.

Abstract: Provided are methods of diagnosing IgA nephropathy in a subject. Optionally, the methods comprise isolating an IgG from the subject and determining whether the IgG binds to a galactose-deficient IgA1. Optionally, the methods comprise providing a biological sample from the subject and detecting in the sample a mutation in a IGH gene, wherein the mutation is in a nucleotide sequence encoding a complementarity determining region 3 (CDR3) of a IGH variable region. Optionally, the methods comprise determining a level of IgG specific for a galactose-deficient IgA1 in the subject. Also provided are methods of treating or reducing the risk of developing IgA nephropathy in a subject.

Abstract: Techniques for illuminating an indoor scene. A directional distribution associated with the indoor scene is received. The indoor scene has a first scene element and a first quadrilateral. The first scene element has a first shading point disposed thereon. The directional distribution is reparametrized such that the first quadrilateral as viewed from the first shading point corresponds to an axis-aligned rectangular region in the reparametrized directional distribution. The scene element is illuminated using one or more samples drawn from the shading point by performing importance sampling based on the reparametrized directional distribution.

Abstract: There is provided a system including a memory storing a software application and a processor configured to execute the software application to transmit a light through a scene, the scene including a medium described by an extinction function, define a fictitious medium described by a fictitious extinction function, determine a path through the medium, the path including a plurality of points, calculate one of a plurality of weights for each of the plurality of points, the one of the plurality of weights corresponding to one minus the ratio of the extinction function to the fictitious extinction function, and estimate a transmittance of the lights through the medium as a product of the plurality of weights.

Abstract: Provided are methods of diagnosing IgA nephropathy in a subject. Optionally, the methods comprise isolating an IgG from the subject and determining whether the IgG binds to a galactose-deficient IgA1. Optionally, the methods comprise providing a biological sample from the subject and detecting in the sample a mutation in a IGH gene, wherein the mutation is in a nucleotide sequence encoding a complementarity determining region 3 (CDR3) of a IGH variable region. Optionally, the methods comprise determining a level of IgG specific for a galactose-deficient IgA1 in the subject. Also provided are methods of treating or reducing the risk of developing IgA nephropathy in a subject.

Abstract: Provided are methods of diagnosing IgA nephropathy in a subject. Optionally, the methods comprise isolating an IgG from the subject and determining whether the IgG binds to a galactose-deficient IgA1. Optionally, the methods comprise providing a biological sample from the subject and detecting in the sample a mutation in a IGH gene, wherein the mutation is in a nucleotide sequence encoding a complementarity determining region 3 (CDR3) of a IGH variable region. Optionally, the methods comprise determining a level of IgG specific for a galactose-deficient IgA1 in the subject. Also provided are methods of treating or reducing the risk of developing IgA nephropathy in a subject.

Abstract: Certain bacteria indigenous to humans produce antimicrobial substances called bacteriocins which inhibit other bacteria, including members of their own species. Mutacins are a class of antibiotic substances made by Streptococcus mutans. Disclosed is the purification and biochemical characterization of a novel lanthionine-containing mutacin peptide from S. mutans. The purified peptide is pH- and temperature-stable and its amino acid composition indicates the presence of lanthionine and &bgr;-methyllanthionine. Also provided are methods of making and using the purified polypeptide.